DSD: document sparse-based denoising algorithm

Short Paper

Abstract

In this paper, we present a sparse-based denoising algorithm for scanned documents. This method can be applied to any kind of scanned documents with satisfactory results. Unlike other approaches, the proposed approach encodes noise documents through sparse representation and visual dictionary learning techniques without any prior noise model. Moreover, we propose a precision parameter estimator. Experiments on several datasets demonstrate the robustness of the proposed approach compared to the state-of-the-art methods on document denoising.

Keywords

Document denoising Sparse representations Sparse dictionary learning Document degradation models 

Notes

Acknowledgements

This work was partially supported by the European project SCANPLAN (A0806017L), the Spanish ConCORDIA Project (TIN2015-70924-C2-2-R) and the Vietnam National University, Hanoi (VNU) under project number QG.18.04.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department Informatics, Faculty of Mathematics Mechanics InformaticsVNU University of ScienceHanoiVietnam
  2. 2.Computer Vision Center, Computer Science Department, Engineering SchoolUniversitat Autònoma de BarcelonaBellaterraSpain
  3. 3.LORIA - UMR 7503Université de LorraineVandoeuvre-lès-NancyFrance

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